/*
 * Copyright 2006-2018 The MZmine 2 Development Team
 *
 * This file is part of MZmine 2.
 *
 * MZmine 2 is free software; you can redistribute it and/or modify it under the terms of the GNU
 * General Public License as published by the Free Software Foundation; either version 2 of the
 * License, or (at your option) any later version.
 *
 * MZmine 2 is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without
 * even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
 * General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License along with MZmine 2; if not,
 * write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301
 * USA
 */

package net.sf.mzmine.modules.peaklistmethods.dataanalysis.clustering.simplekmeans;

import java.util.ArrayList;
import java.util.Enumeration;
import java.util.List;
import java.util.logging.Level;
import java.util.logging.Logger;

import javax.annotation.Nonnull;

import net.sf.mzmine.modules.peaklistmethods.dataanalysis.clustering.ClusteringAlgorithm;
import net.sf.mzmine.modules.peaklistmethods.dataanalysis.clustering.ClusteringResult;
import net.sf.mzmine.modules.peaklistmethods.dataanalysis.clustering.em.EMClustererParameters;
import net.sf.mzmine.parameters.ParameterSet;
import weka.clusterers.SimpleKMeans;
import weka.core.Instance;
import weka.core.Instances;

public class SimpleKMeansClusterer implements ClusteringAlgorithm {

  private Logger logger = Logger.getLogger(this.getClass().getName());

  private static final String MODULE_NAME = "Simple KMeans";

  @Override
  public @Nonnull String getName() {
    return MODULE_NAME;
  }

  @Override
  public ClusteringResult performClustering(Instances dataset, ParameterSet parameters) {

    List<Integer> clusters = new ArrayList<Integer>();
    String[] options = new String[2];
    SimpleKMeans clusterer = new SimpleKMeans();

    int numberOfGroups =
        parameters.getParameter(SimpleKMeansClustererParameters.numberOfGroups).getValue();
    options[0] = "-N";
    options[1] = String.valueOf(numberOfGroups);

    try {
      clusterer.setOptions(options);
      clusterer.buildClusterer(dataset);
      Enumeration<?> e = dataset.enumerateInstances();
      while (e.hasMoreElements()) {
        clusters.add(clusterer.clusterInstance((Instance) e.nextElement()));
      }
      ClusteringResult result = new ClusteringResult(clusters, null, clusterer.numberOfClusters(),
          parameters.getParameter(EMClustererParameters.visualization).getValue());
      return result;

    } catch (Exception ex) {
      logger.log(Level.SEVERE, null, ex);
      return null;
    }
  }

  @Override
  public @Nonnull Class<? extends ParameterSet> getParameterSetClass() {
    return SimpleKMeansClustererParameters.class;
  }
}
